What is unmet demand in a physical store?

It is what shoppers came in for and could not buy: a style that was out of stock, a missing size, a colour or metal you don't offer, a price you don't hit, or something you never ranged. Sales data does not show it, because the till only records what sold.

How can a store capture what shoppers asked for but couldn't find?

Through staff lost-sales logs, clienteling notes kept by client advisers, and questions shoppers ask on in-store screens. Each record should use the same fields, such as store, date, missing attribute, price band, occasion and outcome, so requests can be counted together.

How should merchandisers act on unmet demand?

Stock-outs and size gaps point to replenishment and transfers, location patterns point to allocation, and repeated requests for colours, prices or pieces you don't make point to buying and design. Act on requests that repeat across stores and weeks, not on a single busy day.

Asked for, not stocked

Unmet demand is everything a shopper came in for and could not buy: the size that had sold out, the colour you never made, the occasion piece at a price you don't offer. In a physical store it is almost invisible, because the till only records what sold. Brands that capture it do so in three ways, through staff logs, clienteling notes and on-screen questions, and then act on it through replenishment, allocation and buying.

We have written before about the data gap in physical stores. This guide takes one part of that gap, the "asked for, not stocked" moment, and looks at how to record it and what to do with it.

What counts as unmet demand in a store?

Most merchandisers think of stock-outs first, but they are only one kind. On a shop floor in London or New York, unmet demand usually takes one of five forms.

Stock-outs. The style is in the range, but not in this store today.
Size gaps. The style is here, but not in the shopper's size, or the size run has been broken.
The wrong variant. The shopper wants the dress in black rather than ivory, or the hoop in white gold rather than yellow.
The wrong price. They want something like this, for less: a cocktail dress under $500, a pair of earrings under £300.
Never ranged. They asked for something you don't make at all: a modest evening gown, a men's signet ring, a jacket for a winter trip to Tokyo.

The first two are operational problems. The last three are range problems. They need different owners, which is one reason it helps to record which kind each one is.

Why is lost demand invisible in physical retail?

An online store sees a search that returned nothing. A physical store sees a shopper walk out. Sales data is what statisticians call censored: it tells you how much sold when stock was available, not how much would have sold if it had been.

The scale is large. IHL Group's latest study puts the global cost of inventory distortion at $1.7 trillion, with empty shelves the biggest single driver at $690.9 billion, as summarised by the British Retail Consortium. That figure covers all retail, not fashion alone, but the mechanism is the same.

Shoppers rarely wait. In AlixPartners' 2024 Consumer Sentiment Index of more than 9,000 US fashion consumers, two-thirds said they would leave a store or site and shop with another retailer when an item was out of stock. In an AlixPartners and FDRA footwear survey published in April 2026, 65% of consumers said they had abandoned a purchase because their size was out of stock, close to the 67% who cited price.

Size gaps also distort the data that is left. A 2023 study in Manufacturing & Service Operations Management, using two years of data from 217 stores of a sportswear chain, found that about 51.7% of unmet demand for an out-of-stock shoe size moved to the next size up or down, and about 28.1% became lost sales. So when a size 38 sells out, some of its demand shows up as extra sales of 37 and 39, and some disappears. Read naively, the sales report under-states demand for the missing size and over-states it for its neighbours.

Display rules can hide even more. In their work with Zara, Caro and Gallien modelled a store policy where a product came off display once one of its key sizes sold out. Whatever the rule in your stores, a broken size run makes a style harder to find, and the sales history then looks as if nobody wanted it.

How do stores capture what shoppers asked for?

There are three practical routes. Most brands will use more than one.

Staff logs

The oldest method is a lost-sales log, sometimes called a want book: a sheet, tablet form or field in the point-of-sale system where an associate notes what a shopper asked for and didn't find. It costs almost nothing to start. Its weakness is consistency. On a busy Saturday in Paris, logging is the first task to go, and two associates will describe the same request in different words.

Clienteling notes

In premium fashion and fine jewellery, client advisers already keep notes on their best customers: sizes, upcoming events, pieces they are waiting for. Those notes hold some of the richest demand data a brand has, such as "wants the tennis bracelet in a 16 cm length" or "looking for a navy suit for a June wedding". The problem is that it sits in individual client books and rarely reaches merchandising in a form anyone can count.

Screens and AI questions

When shoppers ask a screen, the question is recorded at the moment it is asked, in the shopper's own words. "Do you have this in green?" "Something for a black-tie dinner under $1,000?" If the stylist on the screen can only answer from the store's stock, every question it cannot answer is a gap, logged with the store, the time and what was offered instead. That is the approach Ateliq takes: its stylist suggests only what the store has, and the weekly report shows what shoppers tried, asked for and could not find, by store.

Method	What it catches well	Where it falls short
Staff log	Stock-outs and size gaps that associates hear about	Patchy when the floor is busy; inconsistent wording
Clienteling notes	Detailed wants of known, high-value clients	Covers few shoppers; locked in personal client books
Screen questions	Requests in the shopper's own words, with time and store	Only covers shoppers who use the screen

What should an unmet-demand record contain?

Whatever the source, a record is only useful if it can be counted alongside the others. Agree a short, fixed set of fields:

Store and date.
Category and style, if it was a specific piece.
The attribute that was missing: size, colour, metal, length, fabric.
Price band the shopper mentioned, in the store's currency.
Occasion, if given: wedding guest, office, black tie, travel.
Type of gap: stock-out, size gap, variant, price or never ranged.
Outcome: bought an alternative, ordered for delivery, left.

Recording the outcome matters. A request that ended in a substitute sale is a different problem from one that ended at the door.

How do you act on unmet demand?

Each type of gap points to a different lever.

Replenishment

Stock-outs and size gaps on styles you already carry are a replenishment issue. Size-level requests show which sizes ran out first and whether the size curve you bought was right for that store. They also justify inter-store transfers in season: if the Milan store keeps hearing requests for a 40 that the Rome store is sitting on, move it before the demand fades.

Allocation

When requests cluster by location, the problem is often where stock went rather than how much was bought. A store in Dubai may hear far more requests for long sleeves and evening lengths than a store in Los Angeles. Feeding that into store allocation pays: in a controlled field experiment, the model-based allocation Caro and Gallien built with Zara increased sales and reduced transfers between stores. Recorded requests give an allocation model a demand signal that sales history, censored by stock-outs, cannot.

Buying

Variant, price and never-ranged gaps belong to the buying and design teams. McKinsey suggests brands keep a larger share of open-to-buy for short-term, demand-led decisions and build a test-and-repeat capability to back best-sellers quickly. A steady stream of unmet requests is exactly the evidence that reserve should be spent on. When the same request keeps coming back, from several stores, over several weeks, it is no longer noise. It is a brief.

What are the common mistakes?

Counting mentions, not shoppers. One determined client asking three times is one request.
Reacting to a single week. Look for requests that repeat across stores and weeks before changing a buy.
Ignoring price. "Like this, but under $400" is a range question, not a stock question.
Not telling the floor. If associates never see a log turn into a re-order, they stop filling it in.

Closing the loop with the shopper

The last step is the one most stores skip: telling the shopper when the thing they wanted arrives. With the shopper's permission, a request can become a follow-up. In Ateliq, shoppers who choose to be remembered keep a style profile, and when a piece they tried is back in their size, Ateliq tells them. Captured this way, unmet demand stops being a lost sale and becomes a sale you can still make.

Asked for, not stocked: how to capture unmet demand in the store